feat: add stats/mskmax

lib/node_modules/@stdlib/stats/mskmax/README.md

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+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# mskmax
+
+> Compute the maximum value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions according to a mask.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var mskmax = require( '@stdlib/stats/mskmax' );
+```
+
+#### mskmax( x, mask\[, options] )
+
+Compute the maximum value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions according to a mask.
+
+```javascript
+var Uint8Array = require( '@stdlib/array/uint8' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0 ] );
+var mask = array( new Uint8Array( [ 0, 0, 1 ] ) );
+
+var y = mskmax( x, mask );
+// returns <ndarray>
+
+var v = y.get();
+// returns 2.0
+```
+
+The function has the following parameters:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or "generic" [data type][@stdlib/ndarray/dtypes].
+-   **mask**: mask [ndarray][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with `x`. If a mask element is `0`, the corresponding element in `x` is considered valid. If a mask element is non-zero, the corresponding element in `x` is ignored.
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+-   **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a real-valued or "generic" [data type][@stdlib/ndarray/dtypes].
+-   **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.
+
+By default, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform a reduction over specific dimensions, provide a `dims` option.
+
+```javascript
+var Uint8Array = require( '@stdlib/array/uint8' );
+var mskmax = require( '@stdlib/stats/mskmax' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0, 4.0 ], {
+    'shape': [ 2, 2 ],
+    'order': 'row-major'
+});
+var mask = array( new Uint8Array( [ 0, 0, 1, 0 ] ), {
+    'shape': [ 2, 2 ],
+    'order': 'row-major'
+});
+var v = ndarray2array( x );
+// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ]
+
+var y = mskmax( x, mask, {
+    'dims': [ 0 ]
+});
+// returns <ndarray>
+
+v = ndarray2array( y );
+// returns [ -1.0, 4.0 ]
+
+y = mskmax( x, mask, {
+    'dims': [ 1 ]
+});
+// returns <ndarray>
+
+v = ndarray2array( y );
+// returns [ 2.0, 4.0 ]
+
+y = mskmax( x, mask, {
+    'dims': [ 0, 1 ]
+});
+// returns <ndarray>
+
+v = y.get();
+// returns 4.0
+```
+
+By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`.
+
+```javascript
+var Uint8Array = require( '@stdlib/array/uint8' );
+var mskmax = require( '@stdlib/stats/mskmax' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0, 4.0 ], {
+    'shape': [ 2, 2 ],
+    'order': 'row-major'
+});
+var mask = array( new Uint8Array( [ 0, 0, 1, 0 ] ), {
+    'shape': [ 2, 2 ],
+    'order': 'row-major'
+});
+
+var v = ndarray2array( x );
+// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ]
+
+var y = mskmax( x, mask, {
+    'dims': [ 0 ],
+    'keepdims': true
+});
+// returns <ndarray>
+
+v = ndarray2array( y );
+// returns [ [ -1.0, 4.0 ] ]
+
+y = mskmax( x, mask, {
+    'dims': [ 1 ],
+    'keepdims': true
+});
+// returns <ndarray>
+
+v = ndarray2array( y );
+// returns [ [ 2.0 ], [ 4.0 ] ]
+
+y = mskmax( x, mask, {
+    'dims': [ 0, 1 ],
+    'keepdims': true
+});
+// returns <ndarray>
+
+v = ndarray2array( y );
+// returns [ [ 4.0 ] ]
+```
+
+By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option.
+
+```javascript
+var Uint8Array = require( '@stdlib/array/uint8' );
+var mskmax = require( '@stdlib/stats/mskmax' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0 ], {
+    'dtype': 'generic'
+});
+var mask = array( new Uint8Array( [ 0, 0, 1 ] ) );
+
+var y = mskmax( x, mask, {
+    'dtype': 'float64'
+});
+// returns <ndarray>
+
+var dt = String( getDType( y ) );
+// returns 'float64'
+```
+
+#### mskmax.assign( x, mask, out\[, options] )
+
+Computes the maximum value of [ndarray][@stdlib/ndarray/ctor] along one or more dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor] according to mask.
+
+```javascript
+var Uint8Array = require( '@stdlib/array/uint8' );
+var mskmax = require( '@stdlib/stats/mskmax' );
+var array = require( '@stdlib/ndarray/array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+
+var x = array( [ -1.0, 2.0, -3.0 ] );
+var mask = array( new Uint8Array( [ 0, 0, 1 ] ) );
+var y = zeros( [] );
+
+var out = mskmax.assign( x, mask, y );
+// returns <ndarray>
+
+var v = out.get();
+// returns 2.0
+
+var bool = ( out === y );
+// returns true
+```
+
+The method has the following parameters:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or generic [data type][@stdlib/ndarray/dtypes].
+-   **mask**: mask [ndarray][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with `x`. If a mask element is `0`, the corresponding element in `x` is considered valid. If a mask element is non-zero, the corresponding element in `x` is ignored.
+-   **out**: output [ndarray][@stdlib/ndarray/ctor].
+-   **options**: function options (_optional_).
+
+The method accepts the following options:
+
+-   **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor].
+-   The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, the function must return an [ndarray][@stdlib/ndarray/ctor] having the same [data type][@stdlib/ndarray/dtypes] as the input [ndarray][@stdlib/ndarray/ctor]. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any supported output [data type][@stdlib/ndarray/dtypes].
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var mskmax = require( '@stdlib/stats/mskmax' );
+
+// Generate an array of random numbers:
+var xbuf = discreteUniform( 25, 0, 20, {
+    'dtype': 'generic'
+});
+
+// Generate a mask array:
+var mbuf = discreteUniform( 25, 0, 1, {
+    'dtype': 'uint8'
+});
+
+// Wrap in ndarrays:
+var x = new ndarray( 'generic', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
+var mask = new ndarray( 'uint8', mbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+console.log( ndarray2array( mask ) );
+
+// Perform a reduction:
+var y = mskmax( x, mask, {
+    'dims': [ 0 ]
+});
+
+// Resolve the output array data type:
+var dt = getDType( y );
+console.log( dt );
+
+// Print the results:
+console.log( ndarray2array( y ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
+
+[@stdlib/ndarray/output-dtype-policies]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/output-dtype-policies
+
+[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
+
+</section>
+
+<!-- /.links -->